I'm a science journalist and author of "Distant Wanderers: the Search for Planets Beyond the Solar System" who writes about over-the-horizon technology, primarily astronomy and space science. I’m a former Hong Kong bureau chief for Aviation Week & Space Technology magazine and former Paris-based technology correspondent for the Financial Times newspaper who has reported from six continents. A 1998 winner in the Royal Aeronautical Society's Aerospace Journalist of the Year Awards (AJOYA), I’ve interviewed Nobel Prize winners and written about everything from potato blight to dark energy. Previously, I was a film and arts correspondent in New York and Europe, primarily for newspaper outlets like the International Herald Tribune, the Boston Globe and Canada's Globe & Mail. Recently, I've contributed to Scientific American.com, Nature News, Physics World, and Yale Environment 360.com. I'm a current contributor to Astronomy and Sky & Telescope and a correspondent for Renewable Energy World. Twitter @bdorminey

For answers, Forbes.com turned to physicist Thomas Bogdan, President of UCAR (the University Corporation for Atmospheric Research) in Boulder, Colorado.

What do you see as the future of weather forecasting?

We’ve made tremendous progress over the last half century and can now predict weather a week or more in advance with fairly good skill. But to move the needle forward, we need to bring more data into the system. That means going to higher computing capacities [to] resolve smaller scales in the models.

An early form of “crowdsourcing”? Here, participants in The National Hail Research Experiment (1972-1976) crane their necks to watch a radiosonde ascending over far northeast Colorado. Credit: copyright University Corporation for Atmospheric Research

What’s going to help you most in making this happen?

Crowdsourcing data for weather forecasting is likely to be one of the exciting new advances. Your automobile [already] measures the [outside] temperature and with some of these OnStar and GPS positioning systems, information about whether you’ve used your anti-skid brakes; whether your lights are on; whether your windshield wipers are on; are things that your automobile can relay to central [collection] points where it can be assimilated into numerical forecast models. That data is critical to nudging those [modeling] systems back to reality.

Does the driver also get customized forecast alerts in return for being part of a mobile weather reporting network?

There’s a tremendous sense that people enjoy having this capability and want to be connected and want their car to be part of a larger system that can alert them in return. You can be told through various apps that the wet weather that you’re going through turns to ice 15 miles ahead. That’s information that you as a driver can then use to decide what to do; to stop or take a different road.

But how do you deal with faulty temperature readings on individual cars?

From the fact that the number that your car is sending in is very different from 42 other cars that have gone through the same area would help us to validate and verify and throw your data out relative to the other [cars].

Is there interest in both the public and private sectors in making this type of road monitoring happen quickly?

There’s definitely interest in working with vehicle manufacturers to use this system in the way I’ve described. And I think it will happen pretty rapidly in the next year or two.

What role will smart phones play in this?

Your cell phone can now temperature and pressure and things like that and there are even some apps out there, particularly one called mPING, a free app that the national weather service has put together so that users can actually register through the app weather conditions that they’re seeing with their cell phone use. With that mPING map you get to see a map of the U.S. with user reports that record things like wind, rain, and snow.

How effective is mPING at the moment?

Right now it’s rather qualitative; it’s not looking for quantitative information, but rather knowing that it’s simply snowing at various locations helps you track the progress of various fronts. It’s beginning to give the average citizen the sense that they can contribute to the greater public good by sharing this information. But we will be able to use data from the next generation of smart phones to collect more precise information.

Are you working on ways to give forecasters real time feedback on accuracy?

Many private sector companies that deliver weather on apps are thinking about a thumbs-up or thumbs-down function. That’s so that if the forecast is [wrong], you can give that forecast a thumbs-down and that be transmitted back to the forecast provider so that they can adjust their models. So, each person with a smart phone can become a validation and verification site for forecasts.

Are social media and crowdsourcing really the key to the future of weather forecasting?

Data is of huge value to us and rather than [immediately] deploying new sensor systems, we should bring in this almost free source of information about changing weather conditions.

Does forecasting accuracy have as much to do with the number of monitoring stations as it does atmospheric science and theory?

It’s both. Data allows us to make better forecasts on one hour to seven or eight day timescale. Data ages with time so any data I take today makes it harder to do something better on a forecast three months out. But we’re investigating looking at ways to come up with forecasts on the two week to two decade time frame. I call it “cleather” for weather and climate.

What’s needed to facilitate “cleather” forecasting?

More physics input from the oceans; the oceans are 70 percent of the planet by surface area. However, GPS technology may also soon give us [new] data about windspeeds and depths of different layers in the global atmosphere.

What puzzles you most about weather and climate?

The sheer variability and extremes. We use climatology when designing infrastructure and vehicles so that they can withstand certain [stresses]. But it seems that we’re seeing more extreme events, like hurricane sandy; the Colorado rain events; the snow in Atlanta.

With such variability, what kind of forecast accuracies can we ultimately hope to achieve?

Most experts will tell you that no matter what you did today, it would be very difficult to get a deterministic forecast, so that I can tell you at 5 pm local time on March 27th, it’s going to be 48 degrees.

So, we have to be more probabilistic. That is, the likelihood of a certain temperature is this and my chances of being off by plus or minus 5 degrees will be so many percent.

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